Data Handling for the Geometric Correction of Large Images

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Abstract
Several geometric distortions are present in remotely sensed images depending on the type of sensors and the object being observed. It is often desirable to compensate for these distortions and store the images in reference to a standard coordinate system. Digital techniques for correction are versatile and introduce a minimum of radiometric errors. The main problems to be considered in this area are the determination of the corrective transformation, resampling, and the management of the large quantities of data. This correspondence considers the last problem. It is shown here that, by a judicious rearrangement of the input data, considerable reductions in the required memory capacity can be achieved. The rearrangement can be accomplished in several stages. The method presented here is amenable to pipeline implementation for processing a continuous stream of images. It can also be used on a relatively small computer with the staging being in time sequence rather than hardware. Examples are shown to illustrate the reductions in overall cost depending on the relative cost of memory and the peripheral devices.

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